Predicting the compressive strength of mortars containing metakaolin by artificial neural networks and fuzzy logic

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dc.contributor.authorSaridemir, Mustafa
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2009
dc.departmentNiğde ÖHÜ
dc.description.abstractArtificial neural networks and fuzzy logic approaches have recently been used to model some of the human activities in many areas of civil engineering applications. Especially from these systems in the model experimental studies, very good results have been obtained. In this research. the models for predicting compressive strength of mortars containing metakaolin at the age of 3, 7, 28, 60 and 90 days have been developed in artificial neural networks and fuzzy logic. For purpose of building these models, training and testing using the available experimental results for 179 specimens produced with 46 different mixture proportions were gathered from the technical literature. The data used in the multilayer feed-forward neural networks and Sugeno-type fuzzy inference models are arranged in a format of five input parameters that cover the age of specimen, metakaolin replacement ratio, water-binder ratio, superplasticizer and binder-sand ratio. According to these input parameters, in the multilayer feed-forward neural networks and Sugeno-type fuzzy inference models, the compressive strength of mortars containing metakaolin are predicted. The training and testing results in the multilayer feed-forward neural networks and Sugeno-type fuzzy inference models have shown that neural networks and fuzzy logic systems have strong potential for predicting compressive strength of mortars containing metakaolin. (C) 2008 Elsevier Ltd. All rights reserved.
dc.identifier.doi10.1016/j.advengsoft.2008.12.008
dc.identifier.endpage927
dc.identifier.issn0965-9978
dc.identifier.issn1873-5339
dc.identifier.issue9
dc.identifier.scopus2-s2.0-67349283336
dc.identifier.scopusqualityQ1
dc.identifier.startpage920
dc.identifier.urihttps://dx.doi.org/10.1016/j.advengsoft.2008.12.008
dc.identifier.urihttps://hdl.handle.net/11480/5020
dc.identifier.volume40
dc.identifier.wosWOS:000266787100020
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorSaridemir, Mustafa
dc.language.isoen
dc.publisherELSEVIER SCI LTD
dc.relation.ispartofADVANCES IN ENGINEERING SOFTWARE
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectMortar
dc.subjectMetakaolin
dc.subjectCompressive strength
dc.subjectNeural network
dc.subjectFuzzy logic
dc.titlePredicting the compressive strength of mortars containing metakaolin by artificial neural networks and fuzzy logic
dc.typeArticle

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